David Vengerov

27 papers B 8C 2Journal 11Unranked 6
YearRankTypeTitle / Venue / Authors
2023 — conf
Dynamic Embedding-based Retrieval for Personalized Item Recommendations at Instacart.
WWW (Companion Volume)
Chuanwei Ruan, Allan Stewart, Han Li, Ryan Ye, David Vengerov, Haixun Wang
2019 J jnl
A Machine Learning Approach to Recommending Files in a Collaborative Work Environment.
ACM SIGOPS Oper. Syst. Rev.
David Vengerov, Sesh Jalagam
2018 — conf
A Two-List Framework for Accurate Detection of Frequent Items in Data Streams.
MLDM (1)
David Vengerov
2018 — conf
Placement of Virtual Containers on NUMA systems: A Practical and Comprehensive Model.
USENIX ATC
Justin R. Funston, Maxime Lorrillere, Alexandra Fedorova, Baptiste Lepers, David Vengerov, Jean-Pierre Lozi, Vivien Quéma
2017 B conf
Dynamic adaptation of user migration policies in distributed virtual environments.
IJCNN
David Vengerov
2015 J jnl
Join Size Estimation Subject to Filter Conditions.
Proc. VLDB Endow.
David Vengerov, Andre Cavalheiro Menck, Mohamed Zaït, Sunil Chakkappen
2015 C conf
The judgment of forseti: economic utility for dynamic heap sizing of multiple runtimes.
ISMM
Callum Cameron, Jeremy Singer, David Vengerov
2011 — conf
FACT: a framework for adaptive contention-aware thread migrations.
Conf. Computing Frontiers
Kishore Kumar Pusukuri, David Vengerov, Alexandra Fedorova, Vana Kalogeraki
2010 J jnl
Adaptive data-aware utility-based scheduling in resource-constrained systems.
J. Parallel Distributed Comput.
David Vengerov, Lykomidis Mastroleon, Declan Murphy, Nicholas Bambos
2009 J jnl
A reinforcement learning framework for utility-based scheduling in resource-constrained systems.
Future Gener. Comput. Syst.
David Vengerov
2009 C conf
Modeling, analysis and throughput optimization of a generational garbage collector.
ISMM
David Vengerov
2008 J jnl
A gradient-based reinforcement learning approach to dynamic pricing in partially-observable environments.
Future Gener. Comput. Syst.
David Vengerov
2008 J jnl
A reinforcement learning framework for online data migration in hierarchical storage systems.
J. Supercomput.
David Vengerov
2007 J jnl
A reinforcement learning approach to dynamic resource allocation.
Eng. Appl. Artif. Intell.
David Vengerov
2007 J jnl
Comprehensive multivariate extrapolation modeling of multiprocessor cache miss rates.
ACM Trans. Comput. Syst.
Ilya Gluhovsky, David Vengerov, Brian O'Krafka
2007 J jnl
Constrained Multivariate Extrapolation Models With Application to Computer Cache Rates.
Technometrics
Ilya Gluhovsky, David Vengerov
2005 — conf
A Reinforcement Learning Framework for Dynamic Resource Allocation: First Results..
ICAC
David Vengerov, Nikolai Iakovlev
2005 J jnl
A fuzzy reinforcement learning approach to power control in wireless transmitters.
IEEE Trans. Syst. Man Cybern. Part B
David Vengerov, Nicholas Bambos, Hamid R. Berenji
2005 — conf
Adaptive Utility-Based Scheduling in Resource-Constrained Systems.
Australian Conference on Artificial Intelligence
David Vengerov
2004 B conf
Using gated experts in fault diagnosis and prognosis.
FUZZ-IEEE
Hamid R. Berenji, Yan Wang, David Vengerov, Reza Langari, Mo Jamshidi
2003 J jnl
A convergent actor-critic-based FRL algorithm with application to power management of wireless transmitters.
IEEE Trans. Fuzzy Syst.
Hamid R. Berenji, David Vengerov
2003 B conf
Co-evolutionary perception-based reinforcement learning for sensor allocation in autonomous vehicles.
FUZZ-IEEE
Hamid R. Berenji, David Vengerov, Jayesh Ametha
2003 B conf
Inductive learning for fault diagnosis.
FUZZ-IEEE
Hamid R. Berenji, Jayesh Ametha, David Vengerov
2002 B conf
Adaptive coordination among fuzzy reinforcement learning agents performing distributed dynamic load balancing.
FUZZ-IEEE
David Vengerov, Hamid R. Berenji, Alex Vengerov
2002 B conf
Using fuzzy reinforcement learning for power control in wireless transmitters.
FUZZ-IEEE
David Vengerov, Hamid R. Berenji
2001 B conf
On Convergence of Fuzzy Reinforcement Learning.
FUZZ-IEEE
Hamid R. Berenji, David Vengerov
2000 B conf
Advantages of cooperation between reinforcement learning agents in difficult stochastic problems.
FUZZ-IEEE
Hamid R. Berenji, David Vengerov